• Journal of the Korea Furniture Society
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• v.21 no.5
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• pp.413-423
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• 2010

The study has been carried to evaluate the wood color, a typical element of visual and decorative effect, for seven major domestic softwoods using L*a*b* and chrominance ($\Delta$E*ab). The result showed that the values of whiteness, redness, and yellowness were positive at both sapwood and heartwood and there were no wood having a small chrominance difference ranged 0~0.5. There was also no wood having a chrominance difference ranging 0.5~3.0. Ginkgo biloba, Pinus koraiensis, and Larix kaempferi wood showed a little different chrominance, Taxus cuspidata, Pinus densiflora for. erecta, and Pinus densiflora wood substantial different chrominance, Juniperus chinensis wood largest different chrominance. It is concluded that the study results could be utilized as a data base in areas of wood craft and furniture and could open a way to substitute foreign imported woods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.520-524
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• 2009

In compressed color images, colors are usually represented by luminance and chrominance (YCbCr) components. Considering characteristics of human vision system, chrominance (CbCr) components are generally represented more coarsely than luminance component. Aiming at possible recovery of chrominance components, we propose a model-based chrominance estimation algorithm where color images are modeled by a Markov random field (MRF). A simple MRF model is here used whose local conditional probability density function (pdf) for a color vector of a pixel is a Gaussian pdf depending on color vectors of its neighboring pixels. Chrominance components of a pixel are estimated by maximizing the conditional pdf given its luminance component and its neighboring color vectors. Experimental results show that the proposed chrominance estimation algorithm is effective for quality improvement of compressed color images such as JPEG and JPEG2000.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2065-2069
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• 2004

This paper presents an adaptive equalizer using finite impulse response (FIR) filter and least-mean square (LMS) algorithm. Herein, the variable step-size technique (VSLMS) for compensating the amplitude of chrominance signal is utilized. The proposed equalizer can be enhanced and compressed the chrominance signal at color subcarrier. The LMS algorithm employed in simplicity structure but gives slow convergence speed. Thus, the variable step-size is very attractive algorithm due to its computational efficiencies and the speed of convergence is improved. In addition, experimental results are carried out by using the modulated 20T sine squared test signal. It is shown here that the adaptive equalizer can be equalized the amplitude chrominance distortion in color television transmission without relative delay distortion.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.74-82
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• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.10a
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• pp.88-91
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• 1984

In component coding, it si well known that a Luminance edge provides better masking of the noise added to chrominance signals. So we propose an adapive DPCM coding system which provides good performance in chromainance signals by using the effect of this masking.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• ETRI Journal
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• v.42 no.2
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• pp.258-271
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• 2020

A correlation exists between luminance samples and chrominance samples of a color image. It is beneficial to exploit such interchannel redundancy for color image compression. We propose an algorithm that predicts chrominance components Cb and Cr from the luminance component Y. The prediction model is trained by supervised learning with Laplacian-regularized least squares to minimize the total prediction error. Kernel principal component analysis mapping, which reduces computational complexity, is implemented on the same point set at both the encoder and decoder to ensure that predictions are identical at both the ends without signaling extra location information. In addition, chrominance subsampling and entropy coding for model parameters are adopted to further reduce the bit rate. Finally, luminance information and model parameters are stored for image reconstruction. Experimental results show the performance superiority of the proposed algorithm over its predecessor and JPEG, and even over JPEG-XR. The compensation version with the chrominance difference of the proposed algorithm performs close to and even better than JPEG2000 in some cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.565-568
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• 2006

In the luminance and chrominance signal, luminance signal creates gray images, and is capable of making each color component compatible with monochrome system. And color components of luminance and chrominance signals are useful to encode or convert the signal because they have low correlation. Each color signal has low correlation statistically, but they are not independent of one another. Therefore, this paper proposes the watermark inserting algorithm for luminance and chrominance signal in the domain of frequency founded on wavelet, considering the interdependent characteristics of color components. Therefore, it can guarantee the robustness and invisible of digital watermark.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.227-236
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• 2003

This paper proposes a modified jointly-blue noise mask (MJBNM) method using the S-CIELAB color measure as digital color halftoning method. Based on an investigation of the relation between the pattern visibility and the chromatic error, of a blue noise pattern, a halftoning method is proposed that reduces the chromatic error, while preserving a high quality blue noise pattern. Accordingly, to reduce the chrominance error, the low-pass filtered error and S-CIELAB chrominance error are both considered during the mask generation procedure and calculated for single and combined patterns. Using the calculated low-pass filtered error, the patterns are then updated by either adding or removing dots from the multiple binary patterns. Finally, the pattern exhibiting the lower S-CIELAB chrominance error is selected. Experimental results demonstrated that the proposed algorithm can produce a visually pleasing half toned image with a lower chrominance error than the JBNM method.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1113-1121
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• 2019

In this paper, we propose the face anti-spoofing method based on combination of luminance and chrominance with convolutional neural networks. The proposed method extracts luminance and chrominance features independently from live and fake faces by using stacked convolutional neural networks and auxiliary networks. Unlike previous methods, an attention module has been adopted to adaptively combine extracted features instead of simply concatenating them. In addition, we propose a new loss function, called the contrast loss, to learn the classifier more efficiently. Specifically, the contrast loss improves the discriminative power of the features by maximizing the distance of the inter-class features while minimizing that of the intra-class features. Experimental results demonstrate that our method achieves the significant improvement for face anti-spoofing compared to existing methods.